Knowledge Resource Center for Ecological Environment in Arid Area
DOI | 10.3390/rs70404565 |
Potential of Space-Borne Hyperspectral Data for Biomass Quantification in an Arid Environment: Advantages and Limitations | |
Zandler, Harald1; Brenning, Alexander2,3; Samimi, Cyrus1,4 | |
通讯作者 | Zandler, Harald |
来源期刊 | REMOTE SENSING
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ISSN | 2072-4292 |
出版年 | 2015 |
卷号 | 7期号:4页码:4565-4580 |
英文摘要 | In spite of considerable efforts to monitor global vegetation, biomass quantification in drylands is still a major challenge due to low spectral resolution and considerable background effects. Hence, this study examines the potential of the space-borne hyperspectral Hyperion sensor compared to the multispectral Landsat OLI sensor in predicting dwarf shrub biomass in an arid region characterized by challenging conditions for satellite-based analysis: The Eastern Pamirs of Tajikistan. We calculated vegetation indices for all available wavelengths of both sensors, correlated these indices with field-mapped biomass while considering the multiple comparison problem, and assessed the predictive performance of single-variable linear models constructed with data from each of the sensors. Results showed an increased performance of the hyperspectral sensor and the particular suitability of indices capturing the short-wave infrared spectral region in dwarf shrub biomass prediction. Performance was considerably poorer in the area with less vegetation cover. Furthermore, spatial transferability of vegetation indices was not feasible in this region, underlining the importance of repeated model building. This study indicates that upcoming space-borne hyperspectral sensors increase the performance of biomass prediction in the world’s arid environments. |
类型 | Article |
语种 | 英语 |
国家 | Germany ; Canada |
收录类别 | SCI-E |
WOS记录号 | WOS:000354789300052 |
WOS关键词 | VEGETATION INDEXES ; AVIRIS DATA ; INFRARED REFLECTANCE ; SEASONAL DYNAMICS ; EO-1 HYPERION ; CROP RESIDUE ; DISCRIMINATION ; IMAGERY ; SOIL ; SENSITIVITY |
WOS类目 | Remote Sensing |
WOS研究方向 | Remote Sensing |
资源类型 | 期刊论文 |
条目标识符 | http://119.78.100.177/qdio/handle/2XILL650/190151 |
作者单位 | 1.Univ Bayreuth, Dept Geog, D-95440 Bayreuth, Germany; 2.Univ Jena, Dept Geog, D-07743 Jena, Germany; 3.Univ Waterloo, Dept Geog & Environm Management, Waterloo, ON N2L 3G1, Canada; 4.BayCEER, Bayreuth Ctr Ecol & Environm Res, D-95440 Bayreuth, Germany |
推荐引用方式 GB/T 7714 | Zandler, Harald,Brenning, Alexander,Samimi, Cyrus. Potential of Space-Borne Hyperspectral Data for Biomass Quantification in an Arid Environment: Advantages and Limitations[J],2015,7(4):4565-4580. |
APA | Zandler, Harald,Brenning, Alexander,&Samimi, Cyrus.(2015).Potential of Space-Borne Hyperspectral Data for Biomass Quantification in an Arid Environment: Advantages and Limitations.REMOTE SENSING,7(4),4565-4580. |
MLA | Zandler, Harald,et al."Potential of Space-Borne Hyperspectral Data for Biomass Quantification in an Arid Environment: Advantages and Limitations".REMOTE SENSING 7.4(2015):4565-4580. |
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